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At least 613 records · Page 34

Forward-backward multiplicity correlations in pp, p+Pb and Pb+Pb collisions with the ATLAS detector

Two-particle pseudorapidity correlations are measured in √s NN = 2.76 TeV Pb+Pb, √s NN = 5.02 TeV p +Pb and √s = 13 TeV pp collisions [ATLAS Collaboration, ATLAS-CONF-2015-051; ATLAS-CONF-2015-020]. Correlation function is measured using charged particles in the pseudorapidity range |η|<2.4 with transverse momentum p T >0.2 GeV, and it is measured as a function of event multiplicity, defined by number of charged particles with |η|<2.5 and p T >0.4 GeV. The correlation function is decomposed into a short-range component (SRC) and a long-range component (LRC). The SRC differs significantly between the opposite-charge pairs and same-charge pairs, and between the three collision systems at similar multiplicity. The LRC is described approximately by 1 + n1n2 in all collision systems over the full multiplicity range. The values of are consistent between the opposite-charge and same-charge pairs, and are similar for the three collision systems at similar multiplicity. The values of and the magnitude of the SRC both follow a power-law dependence on the event multiplicity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Characterising the Higgs boson with ATLAS data from the LHC Run-2

The Higgs boson was discovered by the ATLAS and CMS Collaborations in 2012 using data from Run 1 of the Large Hadron Collider (2010 2012). In Run 2 (2015 2018), about 140 fb -1 of proton–proton collisions at a centre-of-mass energy of 13 TeV were collected by the ATLAS experiment. This review presents the most important Run 2 results obtained by the ATLAS Collaboration regarding the properties of the Higgs boson and its interactions with other particles. The performed studies significantly enhance the understanding of the Higgs boson, while hunting for deviations from the predictions of the Standard Model of particle physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

ATLAS Data Carousel

The ATLAS experiment at CERN's LHC stores detector and simulation data in raw and derived data formats across more than 150 Grid sites world-wide, currently in total about 200PB on disk and 250PB on tape. Data have different access characteristics due to various computational workflows, and can be accessed from different media, such as remote I/O, disk cache on hard disk drives or SSDs. Also, larger data centers provide the majority of offline storage capability via tape systems. For the High-Luminosity LHC (HL-LHC), the estimated data storage requirements are several factors bigger than the present forecast of available resources, based on a flat budget assumption. On the computing side, ATLAS Distributed Computing was very successful in the last years with high performance and high throughput computing integration and in using opportunistic computing resources for the Monte Carlo simulation. On the other hand, equivalent opportunistic storage does not exist. ATLAS started the "Data Carousel" project to increase the usage of less expensive storage, i.e. tapes or even commercial storage, so it is not limited to tape technologies exclusively. Data Carousel orchestrates data processing between workload management, data management, and storage services with the bulk data resident on offline storage. The processing is executed by staging and promptly processing a sliding window of inputs onto faster buffer storage, such that only a small percentage of input data are available at any one time. With this project, we aim to demonstrate that this is the natural way to dramatically reduce our storage cost. The first phase of the project was started in the fall of 2018 and was related to I/O tests of the sites archiving systems. Phase II now requires a tight integration of the workload and data management systems. Additionally, the Data Carousel studies the feasibility to run multiple computing workflows from tape. The project is progressing very well and the results presented in this document will be used before the LHC Run 3.

97 MATHEMATICS AND COMPUTING↗

Rucio beyond ATLAS: experiences from Belle II, CMS, DUNE, EISCAT3D, LIGO/VIRGO, SKA, XENON

For many scientific projects, data management is an increasingly complicated challenge. The number of data-intensive instruments generating unprecedented volumes of data is growing and their accompanying workflows are becoming more complex. Their storage and computing resources are heterogeneous and are distributed at numerous geographical locations belonging to different administrative domains and organisations. These locations do not necessarily coincide with the places where data is produced nor where data is stored, analysed by researchers, or archived for safe long-term storage. To fulfil these needs, the data management system Rucio has been developed to allow the high-energy physics experiment ATLAS at LHC to manage its large volumes of data in an efficient and scalable way. But ATLAS is not alone, and several diverse scientific projects have started evaluating, adopting, and adapting the Rucio system for their own needs. As the Rucio community has grown, many improvements have been introduced, customisations have been added, and many bugs have been fixed. Additionally, new dataflows have been investigated and operational experiences have been documented. In this article we collect and compare the common successes, pitfalls, and oddities that arose in the evaluation efforts of multiple diverse experiments, and compare them with the ATLAS experience. This includes the high-energy physics experiments Belle II and CMS, the neutrino experiment DUNE, the scattering radar experiment EISCAT3D, the gravitational wave observatories LIGO and VIRGO, the SKA radio telescope, and the dark matter search experiment XENON.

Lassnig, Mario↗

BigPanDA monitoring system evolution in the ATLAS Experiment

Monitoring services play a crucial role in the day-to-day operation of distributed computing systems. The ATLAS Experiment at LHC uses the Production and Distributed Analysis workload management system (PanDA WMS), which allows a million computational jobs to run daily at over 170 computing centers of the WLCG and opportunistic resources, utilizing 600k cores simultaneously on average. The BigPanDA monitor is an essential part of the monitoring infrastructure for the ATLAS Experiment that provides a wide range of views, from top-level summaries to a single computational job and its logs. Over the past few years of the PanDA WMS advancement in the ATLAS Experiment, several new components were developed, such as Harvester, iDDS, Data Carousel, and Global Shares. Due to its modular architecture, the BigPanDA monitor naturally grew into a platform where the relevant data from all PanDA WMS components and accompanying services are accumulated and displayed in the form of interactive charts and tables. Moreover the system has been adopted by other experiments beyond HEP. In this paper we describe the evolution of the BigPanDA monitor system, the development of new modules, and the integration process into other experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Accelerating science: The usage of commercial clouds in ATLAS Distributed Computing

The ATLAS experiment at CERN is one of the largest scientific machines built to date and will have ever growing computing needs as the Large Hadron Collider collects an increasingly larger volume of data over the next 20 years. ATLAS is conducting R&D projects on Amazon Web Services and Google Cloud as complementary resources for distributed computing, focusing on some of the key features of commercial clouds: lightweight operation, elasticity and availability of multiple chip architectures. The proof of concept phases have concluded with the cloud-native, vendoragnostic integration with the experiment’s data and workload management frameworks. Google Cloud has been used to evaluate elastic batch computing, ramping up ephemeral clusters of up to O(100k) cores to process tasks requiring quick turnaround. Amazon Web Services has been exploited for the successful physics validation of the Athena simulation software on ARM processors. We have also set up an interactive facility for physics analysis allowing endusers to spin up private, on-demand clusters for parallel computing with up to 4 000 cores, or run GPU enabled notebooks and jobs for machine learning applications. The success of the proof of concept phases has led to the extension of the Google Cloud project, where ATLAS will study the total cost of ownership of a production cloud site during 15 months with 10k cores on average, fully integrated with distributed grid computing resources and continue the R&D projects.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

The ATLAS Electron and Photon Triggers

Electron and photon triggers covering transverse energies from 5 GeV to several TeV are essential for signal selection in a wide variety of ATLAS physics analyses to study Standard Model processes and to search for new phenomena. The ATLAS trigger system is divided in a hardware-based Level-1 trigger and a software-based high-level trigger, both of which were upgraded during the LHC shutdown in preparation for Run 2 operation. To cope with the increasing luminosity and more challenging pile-up conditions at a centre-of-mass energy of 13 TeV, the trigger selections at each level are optimised to control the rates and keep efficiencies high. To achieve this goal multivariate analysis techniques are used. The ATLAS electron and photon triggers and their performance with Run 2 data are presented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Readout and trigger for the AFP detector at ATLAS experiment

AFP, the ATLAS Forward Proton consists of silicon detectors at 205 m and 217 m on each side of ATLAS. In 2016 two detectors in one side were installed. The FEI4 chips are read at 160 Mbps over the optical fibers. The DAQ system uses a FPGA board with Artix chip and a mezzanine card with RCE data processing module based on a Zynq chip with ARM processor running ArchLinux. Finally, in this paper we give an overview of the AFP detector with the commissioning steps taken to integrate with the ATLAS TDAQ. Furthermore first performance results are presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Study of the material of the ATLAS inner detector for Run 2 of the LHC

The ATLAS inner detector comprises three different sub-detectors: the pixel detector, the silicon strip tracker, and the transition-radiation drift-tube tracker. The Insertable B-Layer, a new innermost pixel layer, was installed during the shutdown period in 2014, together with modifications to the layout of the cables and support structures of the existing pixel detector. The material in the inner detector is studied with several methods, using a low-luminosity √s=13 TeV pp collision sample corresponding to around 2.0 nb -1 collected in 2015 with the ATLAS experiment at the LHC. In this paper, the material within the innermost barrel region is studied using reconstructed hadronic interaction and photon conversion vertices. For the forward rapidity region, the material is probed by a measurement of the efficiency with which single tracks reconstructed from pixel detector hits alone can be extended with hits on the track in the strip layers. The results of these studies have been taken into account in an improved description of the material in the ATLAS inner detector simulation, resulting in a reduction in the uncertainties associated with the charged-particle reconstruction efficiency determined from simulation.

47 OTHER INSTRUMENTATION↗

Module and electronics developments for the ATLAS ITk pixel system

The ATLAS experiment is preparing for an extensive modification of its detectors in the course of the planned HL-LHC accelerator upgrade around 2025. The ATLAS upgrade includes the replacement of the entire tracking system by an all-silicon detector (Inner Tracker, ITk). The five innermost layers of ITk will be a pixel detector built of new sensor and readout electronics technologies to improve the tracking performance and cope with the severe HL-LHC environment in terms of occupancy and radiation. Here, the total area of the new pixel system could measure up to 14 m 2 , depending on the final layout choice, which is expected to take place in 2018. In this paper an overview of the ongoing R&D activities on modules and electronics for the ATLAS ITk is given including the main developments and achievements in silicon planar and 3D sensor technologies, readout and power challenges.

47 OTHER INSTRUMENTATION↗

The ATLAS Fast TracKer system

The ATLAS Fast TracKer (FTK) was designed to provide full tracking for the ATLAS high-level trigger by using pattern recognition based on Associative Memory (AM) chips and fitting in high-speed field programmable gate arrays. The tracks found by the FTK are based on inputs from all modules of the pixel and silicon microstrip trackers. The as-built FTK system and components are described, as is the online software used to control them while running in the ATLAS data acquisition system. Also described is the simulation of the FTK hardware and the optimization of the AM pattern banks. An optimization for long-lived particles with large impact parameter values is included. A test of the FTK system with the data playback facility that allowed the FTK to be commissioned during the shutdown between Run 2 and Run 3 of the LHC is reported. The resulting tracks from part of the FTK system covering a limited $\eta$-$\phi$ region of the detector are compared with the output from the FTK simulation. It is shown that FTK performance is in good agreement with the simulation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Analysis of humidity sensitivity of silicon strip sensors for ATLAS upgrade tracker, pre- and post-irradiation

During the prototyping phase of the new ATLAS Inner-Tracker (ITk) strip sensors, a degradation of the device breakdown voltage at high humidity was observed. Although the degradation was temporary, showing a fast recovery in dry conditions, the study of the influence of humidity on the sensor performance was critical to establish counter-measures and handling protocols during production testing in order to ensure the proper performance of the upgraded detector. The work presented here has the objective to study for the first time the breakdown voltage deterioration in presence of ambient humidity of ATLAS ITk production-layout strip sensors with different surface properties, before and after proton, neutron and gamma irradiations. A study of the humidity sensitivity of miniature ATLAS ITk strip sensors, before and after proton irradiations, is also presented to compare the sensitivity of devices with different sizes. The sensors were also exposed for several days to high humidity with the aim to recreate and evaluate the influence of the detector integration environment expected during the Large Hadron Collider (LHC) Long Shutdown 3 (LS3) in 2026, where the sensors will be exposed to ambient humidity for prolonged times.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Fast b -tagging at the high-level trigger of the ATLAS experiment in LHC Run 3

The ATLAS experiment relies on real-time hadronic jet reconstruction and b-tagging to record fully hadronic events containing b-jets. These algorithms require track reconstruction, which is computationally expensive and could overwhelm the high-level-trigger farm, even at the reduced event rate that passes the ATLAS first stage hardware-based trigger. In LHC Run 3, ATLAS has mitigated these computational demands by introducing a fast neural-network-based b-tagger, which acts as a low-precision filter using input from hadronic jets and tracks. It runs after a hardware trigger and before the remaining high-level-trigger reconstruction. This design relies on the negligible cost of neural-network inference as compared to track reconstruction, and the cost reduction from limiting tracking to specific regions of the detector. In the case of Standard Model HH → bb̅bb̅, a key signature relying on b-jet triggers, the filter lowers the input rate to the remaining high-level trigger by a factor of five at the small cost of reducing the overall signal efficiency by roughly 2%.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Performance of the ATLAS forward proton Time-of-Flight detector in Run 2

We present performance studies of the Time-of-Flight (ToF) subdetector of the ATLAS Forward Proton (AFP) detector at the LHC. Efficiencies and resolutions are measured using high-statistics data samples collected at low and moderate pile-up in 2017, the first year when the detectors were installed on both sides of the interaction region. While low efficiencies are observed, of the order of a few percent, the resolutions of the two ToF detectors measured individually are 21 ps and 28 ps, yielding an expected resolution of the longitudinal position of the interaction, z vtx , in the central ATLAS detector of 5.3 ± 0.6 mm. This is in agreement with the observed width of the distribution of the difference between z vtx , measured independently by the central ATLAS tracker and by the ToF detector, of 6.0 ± 2.0 mm.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

The ATLAS trigger system for LHC Run 3 and trigger performance in 2022

The ATLAS trigger system is a crucial component of the ATLAS experiment at the LHC. It is responsible for selecting events in line with the ATLAS physics programme. This paper presents an overview of the changes to the trigger and data acquisition system during the second long shutdown of the LHC, and shows the performance of the trigger system and its components in the proton-proton collisions during the 2022 commissioning period as well as its expected performance in proton-proton and heavy-ion collisions for the remainder of the third LHC data-taking period (2022–2025).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Development of a test system for data links of the ATLAS Inner Tracker (ITk) upgrade silicon pixel detector

This contribution introduces a novel test system developed to evaluate the signal transmission quality in high-speed data links for the 2026 Inner Tracker (ITk) upgrade of the ATLAS experiment. Using an FPGA-based data acquisition (DAQ) framework, the setup can run simultaneous Bit Error Rate (BER) tests for up to 64 channels and generate virtual eye diagrams, for qualifying the ∼26k electrical links at the ATLAS ITk data rate of 1.28 Gb/s. The paper includes results from system calibration, yielding its contribution to the measured losses, and preliminary results from tests of prototype and pre-production assemblies of on-detector links of the three ATLAS ITk Pixel subsystems.

47 OTHER INSTRUMENTATION↗

Cross-correlating Planck with VST ATLAS LRGs: a new test for the ISW effect in the Southern hemisphere

ABSTRACT The integrated Sachs–Wolfe (ISW) effect probes the late-time expansion history of the Universe, offering direct constraints on dark energy. Here, we present our measurements of the ISW signal at redshifts of $\bar{z}=0.35$, 0.55, and 0.68, using the cross-correlation of the Planck cosmic microwave background temperature map with ∼0.5 million luminous red galaxies (LRGs) selected from the VST ATLAS survey. We then combine these with previous measurements based on WMAP and similar SDSS LRG samples, providing a total sample of ∼2.1 million LRGs covering ∼12 000 deg2 of sky. At $\bar{z}=0.35$ and $\bar{z}=0.55$, we detect the ISW signal at 1.2σ and 2.3σ (or 2.6σ combined), in agreement with the predictions of lambda cold dark matter (ΛCDM). We verify these results by repeating the measurements using the BOSS LOWZ and CMASS, spectroscopically confirmed LRG samples. We also detect the ISW effect in three magnitude limited ATLAS + SDSS galaxy samples extending to z ≈ 0.4 at ∼2σ per sample. However, we do not detect the ISW signal at $\bar{z}=0.68$ when combining the ATLAS and SDSS results. Further tests using spectroscopically confirmed eBOSS LRGs at this redshift remain inconclusive due to the current low sky coverage of the survey. If the ISW signal is shown to be redshift dependent in a manner inconsistent with the predictions of ΛCDM, it could open the door to alternative theories such as modified gravity. It is therefore important to repeat the high-redshift ISW measurement using the completed eBOSS sample, as well as deeper upcoming surveys such as DESI and LSST.

Ansarinejad, Behzad↗

A Radiation-Hard 8-Channel 15-Bit 40-MSPS ADC for the ATLAS Liquid Argon Calorimeter Readout

The custom design of a radiation-hardened, 8-channel, 40-MSPS, 15-bit resolution, 14.2-bit dynamic range, 11.4-ENOB ADC data acquisition ASIC fabricated in a commercial 65-nm triple-well CMOS technology is presented. The ADC is developed for and integrates seamlessly into the readout system for the ATLAS liquid argon (LAr) calorimeter in the high-luminosity large hadron collider (HLLHC) upgrade at CERN, which will require a total of 364 936 ADC channels. A three-stage MDAC+SAR pipelined ADC architecture was designed to meet the physics requirements and scientific goals of the ATLAS experiment. The ADC is a fully self-contained data acquisition system that includes foreground calibration, digital data processing, digital control, and supporting circuitry. The measured performance shows the ADC achieves a competitive dynamic range and SNDR, and it meets or exceeds the ATLAS analog requirements. Radiation tolerance and scalability design considerations were implemented at the device-, circuit-, and system-level. Radiation-hardening-by-design techniques used include redundancy for digital circuits, the use of MiM capacitors, and a hybrid RC-DAC for the ADC core. The ADC ASIC was demonstrated to be robust against the effects of the intense radiation expected in the HL-LHC experimental environment.

DAQ↗